Automatic extraction of abnormal regions from lung images
Lee, S. L. A. and Kouzani, A. Z. 2009, Automatic extraction of abnormal regions from lung images, in ISBB 2009 : Proceedings of the 2009 International Symposium on Bioelectronics and Bioinformatics, ISBB, Melbourne, Vic., pp. 80-83.
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ISBB 2009 : Proceedings of the 2009 International Symposium on Bioelectronics and Bioinformatics
Bioelectronics and Bioinformatics Symposium
Place of publication
A system that could automatically extract abnormal lung regions may assist expert radiologists in verifying lung tissue abnormalities. This paper presents an automated lung nodule detection system consisting of five components: acquisition, pre-processing, background removal, detection, and false positives reduction. The system employs a combination of an ensemble classification and clustering methods. The performance of the developed system is compared against some existing counterparts. Based 011 the experimental results, the proposed system achieved a sensitivity of 100% and a false-positives/slice of 0.67 for 30 tested CT images.
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